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On The Goodness of Four Types of Organic Fertilizers Using the Split Plot Design and the Two-Way Block Design with Interactions

Isaac Anthony. A*, Tim Itoro M, Ikpang Ikpang N, Nsikak S

Department of Mathematics and Statistics, Akwa Ibom State University, Ikot Akpaden, Mkpat Enin, Uyo, Akwa Ibom State, Nigeria

Abstract: This study investigated the goodness of four (4) different types of organic fertilizers on crop (maize) yield. Data on kilograms of maize yield for the 2014/2015 planting season from four separate farms in which the four (4) different types of organic fertilizer (poultry droppings, piggery manure, extract from farm product and cassava sediment) were applied were collected from the Department of Soil Science, Akwa Ibom State University. SPLIT PLOT DESIGN and TWO-WAY ANOVA WITH INTERACTIONS models were used in carrying out the analysis. Hypothesis that was tested to ascertain whether there was a significant effect of the four types of organic fertilizer on maize yield indicated that, for both models, there was significant effect. When a pair-wise comparison via Least Significant Difference (LSD) was carried out to determine which of the four types of organic fertilizer was the best. For both models, results showed that extract from farm product was the best.

Keywords: Extract from farm, manure, organic fertilizer, Pair –way comparison, split plot Design

Citation: Isaac Anthony. A, Tim Itoro M, Ikpang Ikpang N, Nsikak S, On The Goodness of Four Types of Organic Fertilizers Using the Split Plot Design and the Two-Way Block Design with Interactions. American Journal of Applied Mathematics and Statistics, 5 (4). 136-144. January 2017. doi:10.12691/ajams-5-4-4

1. Introduction

In agriculture, fertilizer plays a major role when it comes to boosting the productivity of crop yield. The importance of fertilizers (inorganic and organic) in the maintenance and improvement of soil productivity particularly under intensive cultivation has been well documented in various literatures. Fertilizers are classified into two main categories namely; the organic and inorganic fertilizers. The organic fertilizers are valuable byproducts of farming and allied industries derived from plant and animal sources and may contain water, urea, some micronutrients, humid acid etc; while chemical or inorganic fertilizers are fertilizers that are produced from mineral deposits or manufactured from synthetic compounds. They include NPK, Phosphate etc.

In the past few decades, chemical or inorganic fertilizers have widely spread throughout the world and focus and dependence on it by farmers was very high. However, it is now realized that in fields under intensive monoculture which receive heavy applications of chemical fertilizers alone, there is a slow decline in productivity. This has necessitated the growing focus and attention that is today being given to organic manure. Many studies have demonstrated that application of manure (organic fertilizer) will produce crop yield that is equivalent or superior qualitatively and quantitatively to those obtained with chemical fertilizers Xie and MacKenzie [1], Motavalli et al., [2], Eck et al., [3] and Pimpini et al. [4]. Enwall, Philippot and Itallin [5] mentioned that organic fertilizer has long term solution because the nutrient have slow release in the soil with a natural cycle and makes them available to plants for longer time (over months or years). CAST [6] and Zhang J et al [7] in their separate research work, gave reason for the better response of crops to manure than to chemical fertilizer and concluded that it was attributed to the fact that manure supplied nutrient faster than chemical manure, hence, improved soil conditions better than those of commercial fertilizer. Alexander [8] on his part posited that organic manure or fertilizer is a source of many essential elements, even if each organic fertilizer has different concentration of nutrients. Mclnitire et al [9] concluded in their study that organic fertilizers modifies soil’s structure and helps to improve water holding capacity, aeration viability and drainage. Studies by Abeysekerra et al. [10] documented that organic manures enhances the mineral nitrogen content in the soil. Singh and Singh [11]; Ray and Gupta [12]; Sharma et al., [13], Thakur et al. [14] reported that organic matter is an important soil component influencing the physical, chemical and microbiological properties of soil to a great extent and all physical properties of soil are affected by changes in organic matter levels of soil. Sharma, [15] said that the application of organic manures have significant effect on growth and development of crop plants. Silva et al [16] said that organic manure contains the nutrient necessary for better development of crops, that it is a good energy source for soil microorganisms and because of its high content of NPK, it enhances soil fertility. Thomas [17] and Waddington [18] said that organic fertilizer or manure also acts as a substrate for soil microorganism which leads to increased microbial activity thereby increasing the rate of organic material decomposition and releasing of nutrients for plant uptake. According to Nasef et al [19], Palade et al [20], Khahd and Safei [21] and Bhata and Shukla [22], it improves the physical properties of the soil as well as causing significant increase in soil carbon and nitrogen exchange capacity leading to the release of ca, mg, and k which invariably enhances crop yield and productivity.

In their studies, Tuzel [23], Sommerfeldt and Cheng [24] and Cheng et al [25] investigated the effect of cattle manures (animal waste) on soil biological properties and concluded that the use of cattle manures could significantly increase the number of fungi, actinomycetes, bacteria, phosphate-solving bacteria, organic phosphor-mineralizing bacteria, phosphor solubility, mineralization of phosphor as well as enzyme respiration and activity in soil. Youssef, El-Fouly and Mohamedien [26] obtained the best results for Pumice treatment with cattle manure by comparing eight cultivation environments for lettuce. In his experiment using manure in the form of processed organic humus, the quality of tomatoes was observed to have increased compared to the time when manure was merely used. He also showed that the use of poultry manure led to increased plant height and fruit sizes in tomatoes cultivated in low tunnels. Leonard [27] and William et al [28] all concluded that farmers in some cities favor organic manure (urban wastes) since their effect once applied might last for 2 or 3 years. Boateng and Oppong [29] reported improved soil physical properties by the addition of farm-yard manure to it. In Kenya, the value of manure is approximately five times that of its chemical fertilizer equivalent value Lekasi et al. [30]. Bationo and Mokwunye [31] also noted that the addition of organic materials either in the form of manure or crop residues, has beneficial effect on soil’s chemical and physical properties and that the use of farmyard manure can reduce nutrient deficiency in soils. Koppen and Eich [32] noted that K and P deficiencies were reduced when farmyard manure was applied and with rising pH values, the Mn content of the soil declined.

The potential of manure, especially poultry litter, to neutralize soil acidity and raise soil pH has been established. Long term field and greenhouse studies have demonstrated the liming effect of animal manure in acid and neutral soils. Compost is also a slow-release fertilizer. Compared with fresh manure, its N is in a more stable form and not susceptible to loss of NH3 gas [27]. The nutrient value of compost varies a lot and depends on what it is made from. Aside from N, P and K, it supplies varying amounts of secondary nutrients and micronutrients. In addition, some compost contains other growth-promoting substances such as B vitamins, natural hormones and organic acids. Harris et al [33] said that compost that has been made from a variety of materials is likely to provide the best spectrum of nutrients. Lopez-Real [34] in his study, showed that market waste co-composted with saw dust improves crop yield considerably while Cross and Strauss [35] showed that soil nutrients is greatly improved with the use of urban waste.

Some researchers in their studies tested the superiority of organic manure over inorganic fertilizers on some economic and food crops. For instance, Engindeniz and Tuzel [36] experimented on the use of green manure for tomatoes production and concluded that it gives better yield than when commercial manure was used. Singh and Singh [11], Zhang et al [7] and Gaur and Verma [37] demonstrated the response of manure on rice (Oryza sativa) – wheat (Triticum aestivum) production and concluded that it was extremely very significant while Ghafarinejad [38] reported high quality yield of cucumber and other lettuce with the use of organic fertilizer.

Several authors also worked on the comparative analysis of the goodness of some of the organic manures. In their experiment on lettuce, Turhan, Sevgican and Tuzel [39] examined three sources, namely, animal manure, compost, and phosphor-compost. The results indicated that all plant growth factors were affected by the organic fertilizer sources among which the animal manure and phosphor-compost exerted the highest impact on the crop production. The study of three organic fertilizers, namely, cow, swine, and poultry manure, revealed that the use of such fertilizers could increase the lettuce yield up to 37%, 43%, and 98%, respectively. The recycling of nitrogen from poultry manure was found to be 38-82%, urea 51-69%, cow and swine manure 10-25%.

In conclusion, the use of organic fertilizer for farming is fast gaining global acceptance in agriculture. Its main objective is to create a balance between the interconnected systems of soil organisms, plants, animals and humans, improvement of environmental conditions and public health, and very importantly, the need to reduce cost of fertilizing crops.

2. Methodology

Two models, the Split-Plot design model and the Two-way ANOVA with interaction models were adopted for this work. In arriving at the results, SPSS, MINITAB and EXCEL-SOLVER computer softwares were used in the analysis of the data.

2.1. The Model for the Split Plot Design is Given by

; for

[picture] | (1)

•   Is the response of replicate of the level of factor and the level of factor

•   Is the overall mean.

•   Is the random effect of the replicate with

•   Is the fixed effect of the level of factor

•   Is the whole plot error

•   Is the effect of the level of factor

•   Is the fixed interaction effect of the level of factor and level of factor,

•   Is the subplot error, and and are independent

2.2. The Layout of Split Plot Design of an Experiment

Table 1. ANOVA table for Split Plot Design

From the above, we have

Table 2. Complete ANOVA table for Split Plot Design

2.3. Hypothetical Statement

1.  For the fixed effect of the ith level of factor

= 0 for all i.

VS

0 for at least one ; i = 1, 2….

2.  For the fixed effect of the level of factor

= 0 for all j.

VS

0 for at least one ; j = 1, 2….

3.  For the whole plot error

= 0 for all ij.

VS

0 for at least one ; i = 1, 2…, j= 1, 2….

4.  For the random effect of the kth replicate with

= 0 for all k.

VS

0 for at least one ; k = 1, 2….

5.  For the fixed interaction effect of jth random effect of and kth replicate with

= 0 for all jk.

VS

0 for at least one ; j = 1, 2….; k = 1, 2….

The F-value shall be compared with the critical values of, where is the desired level of significance.

2.4. Decision Rule

1. Reject Ho, the hypothesis of no difference or of no relationship between the variables if,

2. Accept Ho, the hypothesis of no difference or of no relationship between the variables if

3. The Model for Two Way ANOVA with Interactions

The model is given as;

; for

[picture] | (2)

•   Is the observation or respond of the treatment in the block in the kth replicate

•   Is the overall mean.

•   Is the true effect of the treatment of factor A

•   Is the true effect of the treatment of factor B

•   Is the interaction between level of factor A and level of factor B

•   Is the error term .

3.1. Hypothetical Statement.

1. For the fixed effect of the ith level of factor A

= 0 for all i.

VS

0 for at least one ; i = 1, 2….

2.  For the fixed effect of the level of factor B

= 0 for all j.

VS

0 for at least one ; j = 1, 2….

3.  For the interaction

= 0 for all ij.

VS

0 for at least one ; i = 1, 2…, j= 1, 2….

The F-value shall be compared with the critical values of, where is the desired level of significance.

3.2. Decision Rule

1. Reject Ho, the hypothesis of no difference or of no relationship between the variables if,

2. Accept Ho, the hypothesis of no difference or of no relationship between the variables if.

Table 3. ANOVA Table for two way ANOVA with interaction

4. Numerical Analysis

4.1. Split Plot Design of an Experiment

The layout of split plot Design

Table 4. Estimates

Table 5. Split Plot ANOVA Table

Decision 4.1.1

The difference in the maize yield by Fertilizer

◊ P- value = .000

Level of significance =0.05

Since P- value = .000 < level of significance =0.05

◊ Conclusion: Ho is rejected hence there is a significant mean difference in the fertilizer

Decision 4.1.2

◊ The difference in the maize yield by main-plot.

P- Value = .000

Level of significance =0.05

Since P- value = .697 > level of significance =0.05

Conclusion: Ho is accepted hence there is no significant mean difference in the main-plot.

Decision. 4.1.3

◊ The difference in the maize yield by sub plot.

P- Value = .000

Level of significance =0.05

Since P- value = .000 < level of significance =0.05

Conclusion: Ho is rejected hence there is a significant mean difference in the sub plot

Decision 4.1.4

◊ The difference in the maize yield by main-plot*sub-plot

◊ P- value = .000

Level of significance =0.05

Since P- value = .263 > level of significance =0.05

Conclusion: Ho is accepted hence there is no significant mean difference in the interaction between the main-plot*sub-plot.

Conclusion: Since the result for the Subplot is statistically significant, this calls for pairwise, comparison test to ascertain the best subplot.

Table 6. Pairwise Comparisons

Based on estimated marginal means

*. The mean difference is significant at the .05 level.

b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).

Findings:

◊  Using pair-wise comparison test as shown above, the result gives the mean difference of -7.375 and P-value = .001 for subplot 1 and subplot 2. Since P=.001 <.05 (level of significance), it means that there is a significant mean difference between the yield of subplot 1 and subplot 2.

◊  Comparing the effect of subplot 1 and subplot 3 the result gives the mean different of -12.462 and p-value = .000. Since P=.000 < .05 (level of significance), it means that there is a significant mean difference between the yield subplot 1 and subplot 3.

◊  Comparing subplot 1 and subplot 4, the result gives the mean different of -19.517 and p-value = .000 Since P=.000 <.05 (level of significance), it means that there is a significant mean difference between the two subplots.

◊  Comparing subplot 2 and subplot 3, the result gives the mean difference of -5.087 and P-value =.024 Since P=.024 <.05(level of significance), it means that there is a significant mean difference between the two subplots.

◊  Comparing subplot 2 and subplot 4, the result gives the mean difference of -12.142 and P-value =.000 Since P=.000 <.05(level of significance), it means that there is a significant mean difference between the two subplots.

◊  Comparing subplot 3 and subplot 4, the result gives the mean difference of -7.054 and P-value =.002 Since P=.002 <.05 (level of significance), it means that there is a significant mean difference between the two subplots.

Conclusion: From the pairwise comparison, it is shown that subplot 4 is the best among the four types of subplots, since the mapping of Subplot 1, Subplot 2, and Subplot 3 produces positive values

4.2. Two- way ANOVA with Interactions

4.2.1. The layout of split plot Design

Table 7. Layout of a Two- Way ANOVA With Interactions

Where the organic fertilizers are poultry droppings (PD), pig manure(PM), extracts from farm product(FP) and cassava sediment(CS).

4.2.2. Testing the Underlying Assumptions

Each of the samples was independently sampled and each of the groups has the same sample size.

4.2 3. Normality Test

H₀: The population is normally distributed

vs

H₁: The population not normally distributed

The test was carried out using both Kolmogorov-Smirnov and Shapiro-Wilk statistic

Table 8. Tests of Normality

Findings: The result in above Table using Shapiro-Wilk gives the probability values of .525, .843, .573 and .680 respectively for Plot 1, Plot 2, Plot 3 and Plot 4. Since each of the probability values is greater than .05 (level of significance), the null hypothesis is retained. Therefore the data is normally distributed and as such satisfies the assumption of normality. The P-values for Kolmogorov-Smirnov were also greater than .05.

4.2.4. Equality of Variance Test

H₀: The variances are equal

VS

H₁: The variances are not equal

This test was carried out using Levene test as shown in the Table below.

Table 9. Test of Homogeneity of Variance

The result of the test ‘based on mean’ gives Levene Statistic of 1.184 and probability value of .324. Since P=.324 >. 05 (level of significance), the null hypothesis is retained meaning that the population variances are equal and as such satisfies the equality of variances assumption.

Table 10. ANOVA Computation for Two way ANOVA with interaction

4.2.5. Findings and Conclusion

◊ The difference in the maize yield by fertilizer (factor)

(3, 48) = 2.80

=10.50

(3,48) = 2.81 < =10.50

Conclusion: Ho is therefore rejected and H1 accepted. Hence we conclude that there is a significant mean difference in the yield of the maize based on the type of fertilizer applied. In other words, fertilizer applied significantly affected crop yield.

◊ The difference in the maize yield by plot.

(3, 48) = 2.80

=0.10

(3, 48) = 2.80 > =0.10

Conclusion: Ho is accepted hence, there is no significant mean difference in the crop yield based on plot.

◊ The difference in the interaction between the fertilizers and crop

(9, 48) = 2.08

=1.02

(9, 48) = 2.08 > =1.02

Conclusion: Ho is accepted hence there is no significant mean difference in the interaction between fertilizer and crop. This implies that there is an interaction between the fertilizers and crops.

Table 11. LSD Pairwise Comparisons

4.2.6. Pair wise comparison within Fertilizers

Since the result for the sample (Fertilizer) is statistically significant, this calls for pairwise comparison test to ascertain the best fertilizer.

◊  Using pairwise comparison test as shown above, the result gives the mean difference of -15. 31 and P-value= .000 for Poultry Dropping and Piggery Manure. Since P=.000<.05 (level of significance), it means that there is a significant mean difference between the yield of Poultry Dropping and Piggery Manure. The negative sign (-) attached to the mean difference between Poultry Dropping and Piggery Manure shows that the mean yield of Piggery Manure is higher than that of Poultry Dropping; as such Piggery Manure is better than Poultry Dropping.

◊  Comparing the effect of Poultry Dropping and Farm product manure on crop yield the result gives p-value = .000. Since P=.000 < .05 (level of significance), it means that there is a significant mean difference between the yield, therefore Farm Product is a better manure than the Poultry Dropping.

◊  Comparing the effect of Poultry dropping and Cassava sediment on crop yield the result gives p-value = .000 Since P=.000 <.05 (level of significance), it means that there is a significant mean difference between the yield. Hence cassava sediment is a better manure than the Poultry Dropping.

◊  Comparing the effect of Piggery Manure and Extract from Farm Product and on crop yield the result gives the mean difference of -3.13 and P-value =.400. Since P=.400>.05(level of significance), it means that there is NO significant mean difference between the yield.

◊  Comparing the effect of Piggery manure and Cassava sediment on crop yield the result gives p-value = .826. Since P=.826 >.05(level of significance), it means that there is NO significant mean difference between the yield.

◊  Comparing the effect of Extract from Farm Product (FP) and Cassava sediment (CS) on crop yield the result gives the mean difference of 2.31 and p-value .533. Since P =.533 >.05 (level of significance), it means that there is NO significant mean difference between the yields. The positive value of 2.31 implies that the yield of Extract from Farm Product is slightly better than that of CS though this is not significant statistically.

Hence, from the pairwise comparison it is shown that extract from farm product is the best among the four types of organic fertilizers applied since the mapping of Farm Product to Poultry Dropping, Piggery Manure and Cassava Sediment produces positive values.

5. Conclusions

1. From the results of the Split Plot Design and Two way ANOVA with Interaction, we see that the four types of organic fertilizer significantly affected crop yield.

2. Comparing the four types of fertilizers which are (poultry dropping, piggery manure, extract from farm product and cassava sediment) in both designs models, the results showed that the yield from extract of farm product has the highest means compared to other organic fertilizers, hence we can conclude that yield from extract of farm product is the best among the four different types of organic fertilizers for the cultivation of maize.

Organic fertilizer has effect on crop yield (maize) and extract of farm product is found to be the best type of organic fertilizer, hence, farmers should therefore adopt extracts of farm produce for maize planting.

References

[1]   | Xie, R. J. and MacKenzie, A. F. 1986. Urea and manure effects on soil nitrogen and corn dry matter yields. Soil Sci. Soc. Am. J. 50: 1504-1509.
[2]   | Motavalli P. P., Kelling, K. A. and Converse, J. C. 1989. First – year nutrient availability from injected dairy manure. J. Environ. Qual. 18: 180-185.
[3]   | Eck, H.V., winter, S. R. and Smith, S. J. 1990. Sugarbeet yield and quality in relation to residual 34 beef feedlot waste. Agron. J. 82: 250-254.
[4]   | F. Pimpini,, L Giardini, M Borim and G. Gianquinto (1992): Effect of Poultry manure and Mineral fertilizer on quality of Crops. Journal of Agricultural science, Cambridge (1992), 118, 215-221.
[5]   | Enwall, K., Philippot, L. and Hallin, S. (2005) Activity and composition of the Denitrifying bacterial community respond differently to long-term fertilization Appl Environ Microbial 71, 8335-8343.
[6]   | CAST. 1996. Integrated animal waste management. Task Force Report. No. 128. Council for Agricultural Science and Technology.
[7]   | Zhang J., Sui, X., Li, B., Su, B., Li, J. and Zhou, D. 1998. An improved water use efficiency for winter wheat grown under reduced irrigation. Fields Crops Research. 59: 91-98.
[8]   | Alexander, Martin 1980: Effects of Acidity on Micro-organisms and Microbial Processes in Soil. 10.1007/978-1-4613-3033-2-27.
[9]   | McIntire J., Bourzat, D. and Pingali, P. 1992. Crop-livestock interaction in sub-Saharan Africa. World Bank regional and sector studies, Washington, DC. USA.

[10]  
Abeysekerra, G.S.K, Sirisena, D.N and Wickrama, U.B 2001: Effect of Green manure Nitrogen sources on weed biomas and grain yield of Rice. Society for the Advancement of Breeding Researches in Asia and Ocienia Tokyo (Japan). Asian Crop Science Association (Australia); Federation of Crop Science Societies of the Phillipines, College, tagana (Phillipines). Food Security and Environment Protection in the New Millennium, Manila (Phillipines). 314.

[11]   | Singh, J.K and Singh, R.K 2000: Effect of Green Manure and Nitogen levels on Crop Yield and Economics of Rice (oryza sativa) –Wheat (Triticum aestivum) Cropping System. Environment and Ecology 18(3) .693-695.
[12]   | Ray, S.S and Gupta R.P 2001: Effect of Green Manuring and Tillage practices on Physical Properties of Puddled loam soil under Rice – Wheat Cropping. Journal of the Indian Society of Soil Sciences 49 (4) 670-678.
[13]   | Sharma, M.P, Bali, S.V and Gupta, D.K. 2001. Soil Fertility and Productivity of Rice – Wheat Cropping System in an Inceptisol as influenced by Integrated Nutrient Management. Indian Journal of agricultural Sciences. 71(2); 82-86.
[14]   | Thakur, R.C, Bindra, A.D, Sood, R.D and Bhargava, M. 1995. Effect of Fertilizer application and green manuring on Physico-chemical Properties of Soil and grain yield of Rice (oryza sativa) –Wheat (Triticum aestivum) Crop Sequence. Indian Journal of agronomy. 40: 4-13.
[15]   | Sharma, H.L. 1983. Studies on the utilization of crop residues, farmyard manure and Nitogen fertilization in Rice – Wheat Cropping System under Sub-temperate Climate. PhD Thesis submitted to HPKV, Palampur (H.P).
[16]   | Silva, T.R.B., Bortoluzzi, T., Silva, C.A.T., Arieira, C.R., 2012. A comparison of poultry litter applied like organic fertilizer and that applied like chemical fertilizer in corn development. Afr. J. Agric. Res. 7 (2), 194-197.
[17]   | Thomas, G.A., 1997. Toxicity identification of poultry litter aqueous leachate. Soil Fert. 8 (61), 251-252.
[18]   | Waddington, S.R., 1998. Organic matter management: from science to practice. Soil Fert. 3 (62), 24-25.
[19]   | Nasef, M.A., Khalil, A.A., Ghazal, F.M., El-Emam, 2004. The residual effect of organic manures with or without bio-fertilizer applied to wheat grown on sandy, calcareous and clay soils on growth and NPK uptake of rocket plants. Egypt J. Agric. Res. 82 (2), 235-246.
[20]   | Palada, M.C., Davis, A.M., Crossman, S.M.A., Rables, C., Chichester, E.A., 2004. Sustainable crop management practices for improving production of culinary herbs in the virgin island. Acta Hort. 629, 289-298.
[21]   | Khalid, K.H.A., Shafei, A.M., 2005. Productivity of dill (Anethum graveolensL.) as influenced by different organic manure rates and sources. Arab Univ. J. Agric. Sci., Ain. Shams Univ., Cairo 13 (3), 901-913.
[22]   | Bhata, K.S., Shukla, K.K., 1982. Effect of continuous application of fertilizers and manure on some physical properties of eroded alluvial soil. J. Ind. Soc. Soil 30, 32-36.
[23]   | Tuzel, Y. (2001). Organic vegetable growing in greenhouses. Regional WG Greenhouse Crop Production in the Mediterranean Region Newsletter, 8, pp. 7-17.
[24]   | Sommerfeldt, T. G. and Chang, C. 1985. Changes in soil properties under annual applications of feedlot manure and different tillage practices. Soil Sci. Soc. Am. J. 49(4): 983-987.
[25]   | Chang, C., Sommerfeldt, T. G. and Entz, T. 1990. Rates of soil chemical changes with eleven annual applications of cattle feedlot manure. Can. J. Soil Sci. 70: 673-681.
[26]   | Youssef, A. M., El-Fouly, A. H. M. & Mohamedien, S. A. (2001). Effect of using organic and chemical fertilizers in fertigation system on yield and fruit quality of tomato. Egyptian Journal of Horticulture, 28(1), pp. 59-77.
[27]   | Leonard, D. 1986. Soil, Crop, and Fertilizer Use: A Field Manual for Development Workers. Under contract with Peace Corps. 4th edition revised and expanded. United State Peace Corps. Information collection and exchange. Reprint R0008.
[28]   | Williams, T. O., Powell, J. M. and Fernandez-Rivera, S. 1995. “Manure availability in relation to sustainable food crop production in semiarid West Africa: Evidence from Niger”, Quarterly J. Internat. Agric.
[29]   | Boateng, J. K and Oppong, J. 1995. Proceedings of Seminar on organic and sedentary agriculture held at the Science and Technology Policy Research Institute (C.S.I.R) Accra. 1-3 Nov, pp 85.
[30]   | Lekasi, J K, J.C Tanner, S.K Kimani and P.J.C Harris. 1998. Manure Management in the Kenya Highlands: Practices and Potential. HDRA, Ryton Organic Gardens, UK.
[31]   | Bationo, A. and Mokwunye, A. U. 1992. Role of manures and crop residue in alleviating soil fertility constraints to crop production: With special reference to the Sahelia and Soudanian zones of West Africa. Fertilizer Research. 29: 217-225.
[32]   | Koppen, D and Eich, D. 1993. Influence from 85-year differentiated organic manuring and mineral fertilization on soil fertility in the static experiment at Bad Lanchstadt. Soils and Fertilizers. 56 (1): 402.

[33]  
Harris, P. J. C., Allison, M., Smith, G., Kindness, H. M. and Kelly, J. 2001. The Potential Use of Waste-stream Products for Soil Amelioration in Peri-urban Interface Agricultural Production Systems. In Waste Composting for Urban and Peri-urban Agriculture (Eds P. Drechsel and D. Kunze) by IWMI and FAO.

[34]   | Lopez-Real, J. M. 1995. Organic Waste and Peri-urban Horticulture. Visit to Kumasi, Ghana, November 1995. Report to National Resources Institute, Chatham, UK. 27pp.
[35]   | Cross, P and Strauss, M. 1985. Health Aspects of Night-soil and Sludge Use in Agriculture and Aquaculture. Report No. 04/85, International Resource Centre for Waste Disposal. Ueberlandstrasse 133. CH-8600. Duebendorf, Switzerland.
[36]   | Engindeniz, S & Tuzel, Y. (2002). The Economic analysis of organic greenhouse tomato production: a case study for Turkey. Agro Food Industry Hi-Tech, 13, pp. 26-30.
[37]   | Gaur, A. C. and Verma, L. N. 1991. Integrated plant nutrition in prevailing crop mixes in India. RAPA report No 7. 60-79.
[38]   | Ghafarinejad, S. A. (2008). Final report of the research proposal on the effect of levels and sources of organic fertilizers on greenhouse cucumber yield and quality in Jiroft region. Jiroft and Kahnooj Shahid Moghbeli Agricultural Research Center.
[39]   | Turhan. E., Sevgican, A. & Tuzel, Y. (1999). Effect of different growing media on greenhouse lettuce growth in soilless culture. Proceeding of the International Symposium on Greenhouse Management for Better Yield and Quality in Mild Winter Climates.
[40]   | Addelman, S. (1964). “Some Two –Level fractional plans with split –plot confounding, Technometrics30, pp. 253-258.
[41]   | Bartlett, M.S. 1935. Discussion of “complete experiment by F. Yates. Journal of Royal statistical society, ser. B, 2.pp. 224-226.
[42]   | Bingham, D. and Sitter, R.S.9 1999. “Minimum Aberration Two-Level Fractional split –plot Design, Technometrics 41, pp. 62-70.
[43]   | Bisgaard, S. 1999. The Design and Analysis of 2k-1x2q-1 split –plot Experiments.ácceted by journal of Quality Technology.
[44]   | Box, G.E.P. and Jones.s,. (1992). Split –plot Design for Robust production experiment. Journal of Applied statistics 19. pp. 3-26.
[45]   | Huang, P. Chen, d. AND Voelkel. J.o. (1998). “Minimum Aberration .Two Level split –plot Designs,” Technometrics 40, pp. 314-326.
[46]   | Letsinger, J.D; Myers, R. H; and Lentner, M. (1996). “Response surface methods for Bi-Randomization structure,” Journal of Quality Technology 28, pp.381-387.
[47]   | Robinson. J. (1967). “Incomplete Split-Plot Designs.” Biometrics 23. pp. 793-802.
[48]   | Robinson, J. (1970). “Blocking incomplete split-plot Design “Biometrika 57, pp. 347-350.